This study employs the attention–interest–search–action–share model and price fairness theory to investigate the configurational factors of consumer price fairness perceptions on online food service platforms. Using lexical analysis and machine learning techniques, 133,378 customer reviews from 244 restaurants listed on the Meituan platform were analyzed. Employing fuzzy-set qualitative comparative analysis, this study examines how configurational variables influence consumer perceptions of price fairness. Contrary to traditional offline food services, the horizontal external reference (reference price) had a non-significant impact on online price fairness perceptions. Instead, consumers’ perceived trust, cultivated through effective marketing and positive reviews, emerged as a pivotal element in fostering favorable price fairness perceptions. Additionally, the synergistic effects of different combinations of perceived quality (taste, service, and environment) and the actual price paid are key to enhancing perceived price fairness. These findings indicate that for merchants on online food service platforms, it is crucial to find the right market position, establish consumer trust, and maintain a balance between perceived quality and actual price paid to foster perceptions of price fairness.

中文翻译：

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在线食品服务平台上的价格公平性感知：使用 fsQCA 和机器学习的数据驱动方法


本研究采用注意力-兴趣-搜索-行动-份额模型和价格公平性理论来调查在线食品服务平台上消费者价格公平感知的配置因素。使用词汇分析和机器学习技术，分析了美团平台上列出的 244 家餐厅的 133,378 条客户评论。本研究采用模糊集定性比较分析，研究了配置变量如何影响消费者对价格公平性的看法。与传统的线下食品服务相反，横向外部参考（参考价格）对在线价格公平性感知没有显著影响。相反，通过有效的营销和正面评价培养的消费者感知信任成为培养有利价格公平观念的关键因素。此外，感知质量（品味、服务和环境）和实际支付的价格的不同组合的协同效应是提高感知价格公平性的关键。这些发现表明，对于在线食品服务平台上的商家来说，找到合适的市场地位、建立消费者信任并在感知质量和实际支付价格之间保持平衡以培养价格公平的感知至关重要。